Exploring the Capabilities of Gibbs Sampling in Pulsar Timing Arrays

Abstract

We explore the use of Gibbs sampling in estimating the noise properties of individual pulsars and illustrate its effectiveness using the NANOGrav 11-year data set. We find that Gibbs sampling noise modeling (GM) is more efficient than the current standard Bayesian techniques (SM) for single pulsar analyses by yielding model parameter posteriors with average effective-sample-size ratio (GM/SM) of 6 across all parameters and pulsars. Furthermore, the output of GM contains posteriors for the Fourier coefficients that can be used to characterize the underlying red noise process of any pulsar's timing residuals, which are absent in current implementations of SM. Through simulations, we demonstrate the potential for such coefficients to measure the spatial cross-correlations between pulsar pairs produced by a gravitational wave background.

arXiv commentPublished

References in corpus (21)

• The NANOGrav 15-year Data Set: Evidence for a Gravitational-Wave Background
• Search for an isotropic gravitational-wave background with the Parkes Pulsar Timing Array
• Searching for the nano-Hertz stochastic gravitational wave background with the Chinese Pulsar Timing Array Data Release I
• The NANOGrav 12.5-year Data Set: Search For An Isotropic Stochastic Gravitational-Wave Background
• The International Pulsar Timing Array second data release: Search for an isotropic Gravitational Wave Background
• On the evidence for a common-spectrum process in the search for the nanohertz gravitational-wave background with the Parkes Pulsar Timing Array
• The NANOGrav Nine-year Data Set: Limits on the Isotropic Stochastic Gravitational Wave Background
• Common-red-signal analysis with 24-yr high-precision timing of the European Pulsar Timing Array: Inferences in the stochastic gravitational-wave background search
• Optimal strategies for gravitational wave stochastic background searches in pulsar timing data
• The stochastic background: scaling laws and time to detection for pulsar timing arrays
• The gravitational-wave background null hypothesis: Characterizing noise in millisecond pulsar arrival times with the Parkes Pulsar Timing Array
• Hyper-efficient model-independent Bayesian method for the analysis of pulsar timing data
• New advances in the Gaussian-process approach to pulsar-timing data analysis
• Identifying and mitigating noise sources in precision pulsar timing data sets
• Time-domain Implementation of the Optimal Cross-Correlation Statistic for Stochastic Gravitational-Wave Background Searches in Pulsar Timing Data
• Realistic sensitivity curves for pulsar timing arrays
• Noise-marginalized optimal statistic: A robust hybrid frequentist-Bayesian statistic for the stochastic gravitational-wave background in pulsar timing arrays
• The NANOGrav 11-Year Data Set: Evolution of Gravitational Wave Background Statistics
• Accurate characterization of the stochastic gravitational-wave background with pulsar timing arrays by likelihood reweighting
• Efficient Gravitational Wave Searches with Pulsar Timing Arrays using Hamiltonian Monte Carlo
• Implementation of an efficient Bayesian search for gravitational wave bursts with memory in pulsar timing array data

Cited by in corpus (8)

• The Need For Speed: Rapid Refitting Techniques for Bayesian Spectral Characterization of the Gravitational Wave Background Using PTAs
• The NANOGrav 15-year Gravitational-Wave Background Methods
• Status Report on Global Pulsar-Timing-Array Efforts to Detect Gravitational Waves
• Use Model Averaging instead of Model Selection in Pulsar Timing
• Solving the PTA Data Analysis Problem with a Global Gibbs Scheme
• Efficient Bayesian inference and model selection for continuous gravitational waves in pulsar timing array data
• Bayesian pulsar timing and noise analysis with Vela.jl: an overview
• Rapid inference for individual binaries and a stochastic background with pulsar timing array data